1. Field of the Invention
The present invention relates to biometrics and more particularly to gait detection.
2. Description of the Related Art
The field of biometrics refers to methodologies used to uniquely recognize people based upon one or more intrinsic physical or behavioral traits. In computer science, in particular, biometrics is used as a form of identity access management and access control. Biometrics also have been used to identify individuals traveling in groups of people while remaining under surveillance. Biometric characteristics can be divided into two main classes: physiological and behavioral. Physiological biometric characteristics are related to the shape of the body and include fingerprint, face recognition, DNA, palm print, hand geometry, iris recognition, and odor/scent. Behavioral biometric characteristics, in turn, are related to the behavior of a person. Examples include typing rhythm, gait, and voice.
Biometric gait recognition refers to the recognition of a person from the manner in which the person walks. Gait recognition has become a recent attractive topic in biometric research and has been categorized into three groups based upon the way in which gait is sensed: machine vision, floor sensor and wearable sensor. In respect to machine vision, gait is captured using one or more video cameras from a distance. Video and image processing techniques are employed to extract gait features for recognition purposes. For example, stride and cadence has been used for both person identification and also verification. By comparison, static body parameters such as the height, the distance between head and pelvis, the maximum distance between pelvis and feet, and the distance between feet has been used for gait recognition.
Most of the machine vision based gait recognition algorithms are based upon the human silhouette. In particular, when using the human silhouette to detect gait, the image background of a person walking is removed and the silhouette of the person is extracted and analyzed for recognition. Thereafter, the average silhouettes appearing over a gait cycle can be computed and the Euclidean distance between two averaged silhouettes can be extracted to compute similarity of gaits. While gait recognition principally relates to the identification of a particular individual, the fundamental assumption of gait recognition remains that a human being walking is the subject of the gait recognition analysis.